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. 2022 Feb 24:13:839362.
doi: 10.3389/fimmu.2022.839362. eCollection 2022.

Energy Metabolism-Related Gene Prognostic Index Predicts Biochemical Recurrence for Patients With Prostate Cancer Undergoing Radical Prostatectomy

Dechao Feng  1 , Xu Shi  1 , Facai Zhang  1 , Qiao Xiong  1 , Qiang Wei  1 , Lu Yang  1
Affiliations

Energy Metabolism-Related Gene Prognostic Index Predicts Biochemical Recurrence for Patients With Prostate Cancer Undergoing Radical Prostatectomy

Dechao Feng et al. Front Immunol. .

Abstract

Background: We aimed to construct and validate an energy metabolism-related gene prognostic index (EMRGPI) to predict biochemical recurrence (BCR) in patients undergoing radical prostatectomy.

Methods: We used Lasso and COX regression analysis to orchestrate the EMRGPI in the TCGA database, and the prognostic value of EMRGPI was further validated externally using the GSE46602. All analyses were conducted with R version 3.6.3 and its suitable packages.

Results: SDC1 and ADH1B were finally used to construct the risk formula. We classified the 430 tumor patients in the TCGA database into two groups, and patients in the high-risk group had a higher risk of BCR than those in the low-risk group (HR: 1.98, 95%CI: 1.18-3.32, p=0.01). Moreover, in the GSE46602, we confirmed that the BCR risk in the high-risk group was 3.86 times higher than that in the low-risk group (95%CI: 1.61-9.24, p=0.001). We found that patients in the high-risk group had significantly higher proportions of residual tumor, older age, and T stage. SDC1 and ADH1B were significantly expressed low in the normal tissues when compared to the tumor tissues, which were opposite at the protein level. The spearman analysis showed that EMRGPI was significantly associated with B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, dendritic cells, stromal score, immune score, and estimate score. In addition, the EMRGPI was positively associated with the 54 immune checkpoints, among which CD80, ADORA2A, CD160, and TNFRSF25 were significantly related to the BCR-free survival of PCa patients undergoing RP.

Conclusions: The EMRGPI established in this study might serve as an independent risk factor for PCa patients undergoing radical prostatectomy.

Keywords: biochemical recurrence; energy metabolism; immune checkpoint; prostate cancer; tumor immune microenvironment.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Identification of EMRGPI and its clinical values. (A) gene cluster plot showing the process of WGCNA analysis; (B) modules and phenotype showing 2183 genes in the black, greenyellow, and pink modules which were highly related to tumor; (C) Venn plot showing the intersection of tumor-related genes, DEGs and energy metabolism-related genes; (D) variables screening through the Lasso regression analysis where the lambda value was 0.0185; (E) trajectory diagram of the 11 genes identified through the Lasso regression analysis; (F) forest plot showing the COX regress analysis of genes associated with BCR-free survival; (G) Kaplan-Meier curve showing survival difference of high- and low-risk group in the TCGA database; (H) Kaplan-Meier curve showing survival difference of high- and low-risk group in the GSE46602 (17); (I) ROC curve showing the diagnostic ability of EMRGPI in distinguishing BCR from no BCR; (J) Time-dependent ROC curve showing the diagnostic ability of EMRGPI in distinguishing BCR from no BCR; (K) Gene interacted with ADH1B and SDC1. BCR, biochemical recurrence; DEGs, differentially expressed genes; EMRGPI, energy metabolism-related gene prognostic index; WGCNA, weighted gene co-expression network analysis; mRNA, message RNA; ROC, receiver operating characteristic curve. prostate cancer patients were divided into high- and low-risk groups according to the median of the EMRGPI score.
Figure 2
Figure 2
Differential expression of SDC1 and ADH1B and TME analysis. (A) volcano plot showing differentially expressed genes between tumor and normal tissues; (B) differential expression of SDC1 at protein level in the HPA database (19, 20); (C) differential expression of ADH1B at protein level in the HPA database (19, 20); (D) the correlations between EMRGPI and TME indicators; (E) the correlations between EMRGPI and immune checkpoints; (F) Kaplan-Meier curve showing survival difference of high- and low-expression of CD80 in the TCGA database; (G) Kaplan-Meier curve showing survival difference of high- and low-expression of ADORA2A in the TCGA database; (H) Kaplan-Meier curve showing survival difference of high- and low-expression of CD160 in the TCGA database; (I) Kaplan-Meier curve showing survival difference of high- and low-expression of TNFRSF25 in the TCGA database. BCR, biochemical recurrence; EMRGPI, energy metabolism-related gene prognostic index; TME, tumor immune microenvironment.
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